Use generic train config overrides

AGENTS.md

@@ -66,8 +66,11 @@ Short fixed-iteration run:
 ```bash
 uv run lost-cities-deep-cfr train \
   --config configs/deep_cfr/deep_cfr_selfplay_full_depth_slot_playability.yaml \
-  --iterations 100 \
+  --set run.iterations=100 \
-  --save-latest-only
+  --set run.max_hours=null \
+  --set run.max_iterations=null \
+  --set checkpoint.save_latest_only=true \
+  --set checkpoint.save_every_iteration=false
 ```
 
 Use explicit run directories for experiments. Put Deep CFR runs under
@@ -77,8 +80,8 @@ Use explicit run directories for experiments. Put Deep CFR runs under
 RUN_DIR="runs/deep_cfr/$(date +%Y-%m-%d_%H%M%S)_deep_cfr_experiment_name"
 uv run lost-cities-deep-cfr train \
   --config configs/deep_cfr/deep_cfr_selfplay_full_depth_slot_playability.yaml \
-  --checkpoint-dir "$RUN_DIR" \
+  --set checkpoint.directory="$RUN_DIR" \
-  --max-iterations 100
+  --set run.max_iterations=100
 ```
 
 Date-prefixed examples:
@@ -86,16 +89,23 @@ Date-prefixed examples:
 - `runs/deep_cfr/YYYY-MM-DD_HHMMSS_deep_cfr_100iter`
 - `runs/deep_cfr/YYYY-MM-DD_HHMMSS_deep_cfr_unbounded`
 
-Useful train overrides:
+Useful train controls:
 
 - `--resume`: resume from `<checkpoint-dir>/latest.pt`.
 - `--resume PATH`: resume from a specific checkpoint.
-- `--exact-resume`: require checkpoint config compatibility for exact resume.
+- `--device DEVICE`: override the trainer device for this invocation.
-- `--no-save`: disable checkpoint writes.
+- `--set PATH=VALUE`: override config fields. It is repeatable and parses
-- `--save-latest-only`: keep only `latest.pt`.
+  values as YAML, e.g. `--set traversal.num_workers=4` or
-- `--save-iteration-interval N`: archive every N iterations.
+  `--set run.max_hours=null`.
-- `--set PATH=VALUE`: override arbitrary config fields, e.g.
+
-  `--set traversal.num_workers=4`.
+Common `--set` overrides:
+
+- `--set checkpoint.exact_resume=true`: require checkpoint config compatibility.
+- `--set checkpoint.save_latest=false --set checkpoint.save_every_iteration=false
+  --set checkpoint.save_iteration_interval=0`: disable checkpoint writes.
+- `--set checkpoint.save_latest_only=true --set checkpoint.save_every_iteration=false`:
+  keep only `latest.pt`.
+- `--set checkpoint.save_iteration_interval=N`: archive every N iterations.
 
 ## Long Runs
 
@@ -147,8 +157,8 @@ checkpoint:
 ```
 
 `latest.pt` is updated continuously; archive checkpoints are written every 100
-iterations. If disk is tight, prefer `--save-latest-only` or increase
+iterations. If disk is tight, prefer `--set checkpoint.save_latest_only=true` or
-`save_iteration_interval`.
+increase `save_iteration_interval`.
 
 ## Evaluation And Analysis
 

src/coolrl_lost_cities/games/classic/deep_cfr/cli.py

@@ -80,52 +80,6 @@ def _resolve_resume_path(config: DeepCFRConfig, resume: str | None) -> str | Non
 
 def _train_overrides_from_args(args: argparse.Namespace) -> dict[str, Any]:
     overrides: dict[str, Any] = {}
-    if args.no_save and (args.save_latest_only or args.save_iteration_interval is not None):
-        raise ValueError("--no-save cannot be combined with checkpoint save overrides")
-    run_overrides = overrides.setdefault("run", {})
-    if args.iterations is not None:
-        run_overrides["iterations"] = args.iterations
-        if args.max_hours is None and args.max_iterations is None:
-            run_overrides["max_hours"] = None
-            run_overrides["max_iterations"] = None
-    if args.max_hours is not None:
-        run_overrides["max_hours"] = args.max_hours
-    if args.max_iterations is not None:
-        run_overrides["max_iterations"] = args.max_iterations
-    if args.seed is not None:
-        run_overrides["seed"] = args.seed
-    if args.traversals_per_iteration is not None:
-        traversal_overrides = overrides.setdefault("traversal", {})
-        traversal_overrides["traversals_per_iteration"] = args.traversals_per_iteration
-        traversal_overrides["traversals_per_player"] = None
-    if args.num_workers is not None:
-        overrides.setdefault("traversal", {})["num_workers"] = args.num_workers
-    if args.checkpoint_dir is not None:
-        overrides.setdefault("checkpoint", {})["directory"] = args.checkpoint_dir
-    if args.eval_every is not None:
-        overrides.setdefault("evaluation", {})["eval_every"] = args.eval_every
-    if args.eval_games is not None:
-        overrides.setdefault("evaluation", {})["games"] = args.eval_games
-    if args.regret_fallback is not None:
-        overrides.setdefault("regret_matching", {})["all_negative_fallback"] = args.regret_fallback
-    if args.training_weighting is not None:
-        overrides.setdefault("training_weighting", {})["mode"] = args.training_weighting
-    if args.no_save:
-        checkpoint_overrides = overrides.setdefault("checkpoint", {})
-        checkpoint_overrides["save_latest"] = False
-        checkpoint_overrides["save_every_iteration"] = False
-        checkpoint_overrides["save_iteration_interval"] = 0
-    if args.save_latest_only:
-        checkpoint_overrides = overrides.setdefault("checkpoint", {})
-        checkpoint_overrides["save_latest"] = True
-        checkpoint_overrides["save_latest_only"] = True
-        checkpoint_overrides["save_every_iteration"] = False
-    if args.save_iteration_interval is not None:
-        overrides.setdefault("checkpoint", {})["save_iteration_interval"] = (
-            args.save_iteration_interval
-        )
-    if args.exact_resume:
-        overrides.setdefault("checkpoint", {})["exact_resume"] = True
     for assignment in getattr(args, "config_overrides", None) or ():
         _set_path_override(overrides, assignment)
     return overrides
@@ -249,39 +203,19 @@ def main(argv: list[str] | None = None) -> None:
 
     train = subparsers.add_parser("train")
     train.add_argument("--config")
-    train.add_argument("--iterations", type=int)
-    train.add_argument("--max-hours", type=float)
-    train.add_argument("--max-iterations", type=int)
-    train.add_argument("--traversals-per-iteration", type=int)
-    train.add_argument("--num-workers")
-    train.add_argument("--checkpoint-dir")
     train.add_argument("--resume", nargs="?", const=_RESUME_LATEST, default=None)
-    train.add_argument("--exact-resume", action="store_true")
     train.add_argument("--device")
-    train.add_argument("--eval-every", type=int)
-    train.add_argument("--eval-games", type=int)
-    train.add_argument(
-        "--regret-fallback",
-        choices=("uniform", "argmax_tiebreak"),
-        help="Override regret_matching.all_negative_fallback.",
-    )
-    train.add_argument(
-        "--training-weighting",
-        choices=("none", "lcfr", "dcfr"),
-        help="Override training_weighting.mode.",
-    )
-    train.add_argument("--seed", type=int)
     train.add_argument(
         "--set",
         action="append",
         default=[],
         dest="config_overrides",
         metavar="PATH=VALUE",
-        help="Override any config field using dotted paths, e.g. traversal.sampling_mode=external.",
+        help=(
+            "Override config fields using dotted paths. Repeatable. VALUE is parsed as "
+            "YAML, e.g. --set traversal.num_workers=4 --set run.max_hours=null."
+        ),
     )
-    train.add_argument("--no-save", action="store_true")
-    train.add_argument("--save-latest-only", action="store_true")
-    train.add_argument("--save-iteration-interval", type=int)
     train.add_argument(
         "--wandb",
         action="store_true",

tests/games/classic/test_deep_cfr_trainer.py

@@ -74,26 +74,24 @@ def test_deep_cfr_loads_mapped_legacy_reproduction_config() -> None:
     )
 
 
-def test_deep_cfr_train_cli_count_overrides_disable_duration_limits() -> None:
+def test_deep_cfr_train_cli_accepts_run_and_traversal_config_overrides() -> None:
     args = type(
         "Args",
         (),
         {
-            "iterations": 1,
+            "config_overrides": [
-            "max_hours": None,
+                "run.iterations=1",
-            "max_iterations": None,
+                "run.max_hours=null",
-            "seed": None,
+                "run.max_iterations=null",
-            "traversals_per_iteration": 1,
+                "traversal.traversals_per_iteration=1",
-            "num_workers": "0",
+                "traversal.traversals_per_player=null",
-            "checkpoint_dir": None,
+                "traversal.num_workers=0",
-            "eval_every": None,
+                "regret_matching.all_negative_fallback=argmax_tiebreak",
-            "eval_games": None,
+                "training_weighting.mode=lcfr",
-            "regret_fallback": "argmax_tiebreak",
+                "checkpoint.save_latest=false",
-            "training_weighting": "lcfr",
+                "checkpoint.save_every_iteration=false",
-            "no_save": True,
+                "checkpoint.save_iteration_interval=0",
-            "save_latest_only": False,
+            ],
-            "save_iteration_interval": None,
-            "exact_resume": False,
         },
     )()
     config = load_config("configs/deep_cfr/deep_cfr_selfplay_full_depth_slot_playability.yaml")
@@ -123,21 +121,12 @@ def test_deep_cfr_train_cli_checkpoint_save_overrides() -> None:
         "Args",
         (),
         {
-            "iterations": None,
+            "config_overrides": [
-            "max_hours": None,
+                "checkpoint.save_latest=true",
-            "max_iterations": None,
+                "checkpoint.save_latest_only=true",
-            "seed": None,
+                "checkpoint.save_every_iteration=false",
-            "traversals_per_iteration": None,
+                "checkpoint.save_iteration_interval=1",
-            "num_workers": None,
+            ],
-            "checkpoint_dir": None,
-            "eval_every": None,
-            "eval_games": None,
-            "regret_fallback": None,
-            "training_weighting": None,
-            "no_save": False,
-            "save_latest_only": True,
-            "save_iteration_interval": 1,
-            "exact_resume": False,
         },
     )()
 
@@ -154,21 +143,6 @@ def test_deep_cfr_train_cli_accepts_generic_config_overrides() -> None:
         "Args",
         (),
         {
-            "iterations": None,
-            "max_hours": None,
-            "max_iterations": None,
-            "seed": None,
-            "traversals_per_iteration": None,
-            "num_workers": None,
-            "checkpoint_dir": None,
-            "eval_every": None,
-            "eval_games": None,
-            "regret_fallback": None,
-            "training_weighting": None,
-            "no_save": False,
-            "save_latest_only": False,
-            "save_iteration_interval": None,
-            "exact_resume": False,
             "config_overrides": [
                 "traversal.sampling_mode=external",
                 "traversal.max_depth=null",